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Python Data Visualization & Interactive Dashboards

Step into data visualization and build interactive dashboards with Python. Impress potential employers with your skill in gathering, manipulating, and analyzing real-life data through hands-on projects. Deploy your work online and show your expertise in coding and analysis.

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Class Description

Description

Build dynamic dashboards and interactive data visualizations using Python, then deploy them online to demonstrate your skills to potential employers.

This course equips you with the knowledge and practical skills to gather, manipulate, and analyze real-world datasets through comprehensive hands-on projects. The curriculum begins with essential Python data manipulation libraries such as NumPy and Pandas, then progresses to visualization solutions with a strong emphasis on creating compelling and informative visual presentations. You will master both traditional visualization tools, including Matplotlib and Seaborn, as well as modern interactive platforms like Plotly and Dash Enterprise, which enable you to build sophisticated, dynamic dashboards that effectively communicate data insights.

Throughout the course, you gain practical experience by completing real-world projects that you can deploy online using Heroku servers and GitHub repositories. Publishing an analytical project on GitHub demonstrates your proficiency with professional data science techniques and fulfills key requirements for technical employment. Employers review your coding methodology and analytical approaches through these public portfolios, making hands-on project experience a critical component of career development in data science.

Each course day follows a structured two-part format. The first part introduces new concepts and techniques through direct instruction and explanation. The second part immediately applies these concepts to a project you select, whether based on your professional field, personal interests, or academic pursuits. Throughout this process, your instructor assists with identifying appropriate datasets, teaching industry best practices, and providing guidance on writing efficient and professional code.

Required Prior Knowledge: You must complete the Python for Data Science Bootcamp before enrolling in this course. This prerequisite ensures you have the foundational Python skills and data science knowledge necessary for success.

Learn more about Python Data Visualization & Interactive Dashboards at Practical Programming.

Syllabus

Conducting Advanced Exploratory Analysis

  • NumPy array
  • Array containers
  • Indexing on an array
  • Broadcasting
  • Reshaping
  • Universal functions
  • Series
  • DataFrame
  • Slicing DataFrame
  • Filtering DataFrame
  • Understanding JSON
  • Working with APIs

Building Dashboards and Visualizing Data

  • Dash Callbacks
  • Client Callbacks
  • Pattern Callbacks
  • Dash core components
  • Date Picker
  • Date Range
  • More Dash Components
  • Graph
  • Dash HTML Components
  • Dash Styling

Presenting Information with Conviction and Persuasion

  • Dash Styling
  • Dash and Bootstrap
  • Creating your own Components
  • Deployment
  • Make a live presentation

Refund Policy

To reschedule or cancel, email us at [email protected]

All courses include a non-refundable registration fee (10% of the undiscounted course price).

  • Students may cancel up to 11 business days before the class/program start date and receive a refund, less the registration fee.
  • Cancellations within 11 business days are not permitted; however, students may reschedule up to 4 business days before the class start date.

Note: Any refunds must be requested within 180 days from the original payment date; courses rescheduled within 11 business days of the start date are not eligible for refunds.

Reviews of Classes at Practical Programming (330)

(4.5-star rating across 330 reviews)

This class: 4.0 out of 5 from 2 reviews

  • Python Data Visualization & Interactive Dashboards

    An illuminating course on Neural Networks and their implementation in Python. The instructor explains some of the theory at an approachable and high-level of detail.
  • Python Data Visualization & Interactive Dashboards

    Good course overall as an intro to NN & ML. Instructor was knowledgeable.
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Practical Programming

Practical Programming offers programming classes and workshops for individuals of all skill levels who are interested in learning Python coding. It is suitable for beginners and those looking to start a career in programming or build dynamic web applications using Python.

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